Overview

Dataset statistics

Number of variables14
Number of observations907
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.3 KiB
Average record size in memory112.1 B

Variable types

DateTime1
Numeric13

Alerts

overall_rate is highly overall correlated with age_16_17_rate and 11 other fieldsHigh correlation
age_16_17_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_16_19_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_18_19_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_16_24_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_20_24_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_25_34_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_25_54_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_35_44_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_45_54_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_20plus_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_25plus_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
age_55plus_rate is highly overall correlated with overall_rate and 11 other fieldsHigh correlation
date has unique valuesUnique

Reproduction

Analysis started2023-08-22 18:17:49.027043
Analysis finished2023-08-22 18:18:05.313948
Duration16.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

date
Date

UNIQUE 

Distinct907
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum1948-01-01 00:00:00
Maximum2023-07-01 00:00:00
2023-08-22T13:18:05.455972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:05.589591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

overall_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7158765
Minimum2.5
Maximum14.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:05.719619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile3.5
Q14.4
median5.5
Q36.75
95-th percentile9
Maximum14.7
Range12.2
Interquartile range (IQR)2.35

Descriptive statistics

Standard deviation1.7076414
Coefficient of variation (CV)0.29875407
Kurtosis1.038643
Mean5.7158765
Median Absolute Deviation (MAD)1.1
Skewness0.83950259
Sum5184.3
Variance2.916039
MonotonicityNot monotonic
2023-08-22T13:18:05.855650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.4 34
 
3.7%
5.7 33
 
3.6%
5.6 32
 
3.5%
5.9 29
 
3.2%
3.8 28
 
3.1%
5.5 25
 
2.8%
5 25
 
2.8%
5.2 24
 
2.6%
5.8 23
 
2.5%
6 21
 
2.3%
Other values (73) 633
69.8%
ValueCountFrequency (%)
2.5 2
 
0.2%
2.6 3
 
0.3%
2.7 3
 
0.3%
2.8 1
 
0.1%
2.9 4
 
0.4%
3 4
 
0.4%
3.1 7
0.8%
3.2 3
 
0.3%
3.3 1
 
0.1%
3.4 15
1.7%
ValueCountFrequency (%)
14.7 1
 
0.1%
13.2 1
 
0.1%
11 1
 
0.1%
10.8 2
0.2%
10.4 3
0.3%
10.3 1
 
0.1%
10.2 2
0.2%
10.1 3
0.3%
10 1
 
0.1%
9.9 4
0.4%

age_16_17_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct202
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.871555
Minimum6.5
Maximum31.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:05.986301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.5
5-th percentile10
Q115.2
median17.8
Q320.4
95-th percentile26.2
Maximum31.7
Range25.2
Interquartile range (IQR)5.2

Descriptive statistics

Standard deviation4.5389103
Coefficient of variation (CV)0.253974
Kurtosis0.37413959
Mean17.871555
Median Absolute Deviation (MAD)2.6
Skewness0.25799739
Sum16209.5
Variance20.601707
MonotonicityNot monotonic
2023-08-22T13:18:06.116281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17.4 16
 
1.8%
18.9 15
 
1.7%
17.8 14
 
1.5%
17.5 14
 
1.5%
18.3 14
 
1.5%
18.8 14
 
1.5%
19.7 13
 
1.4%
20 13
 
1.4%
19.3 12
 
1.3%
21 12
 
1.3%
Other values (192) 770
84.9%
ValueCountFrequency (%)
6.5 1
 
0.1%
7.4 2
0.2%
7.5 1
 
0.1%
7.6 2
0.2%
8 1
 
0.1%
8.1 3
0.3%
8.2 1
 
0.1%
8.3 1
 
0.1%
8.4 1
 
0.1%
8.5 2
0.2%
ValueCountFrequency (%)
31.7 1
 
0.1%
31.3 1
 
0.1%
31 1
 
0.1%
30.7 1
 
0.1%
30.6 1
 
0.1%
30.3 3
0.3%
30 1
 
0.1%
29.8 2
0.2%
29.7 1
 
0.1%
29.6 2
0.2%

age_16_19_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct183
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.006064
Minimum6.4
Maximum32.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:06.243310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.4
5-th percentile9.7
Q113.5
median16
Q318
95-th percentile23.9
Maximum32.7
Range26.3
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.9538084
Coefficient of variation (CV)0.24701941
Kurtosis0.62045129
Mean16.006064
Median Absolute Deviation (MAD)2.2
Skewness0.39283133
Sum14517.5
Variance15.632601
MonotonicityNot monotonic
2023-08-22T13:18:06.372340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.1 18
 
2.0%
16.3 18
 
2.0%
17.1 17
 
1.9%
16.8 16
 
1.8%
15.9 16
 
1.8%
13.9 14
 
1.5%
16 14
 
1.5%
16.6 13
 
1.4%
14.6 13
 
1.4%
16.5 13
 
1.4%
Other values (173) 755
83.2%
ValueCountFrequency (%)
6.4 1
 
0.1%
6.7 3
0.3%
6.9 2
0.2%
7 1
 
0.1%
7.1 1
 
0.1%
7.3 2
0.2%
7.4 1
 
0.1%
7.6 3
0.3%
7.7 1
 
0.1%
7.9 1
 
0.1%
ValueCountFrequency (%)
32.7 1
 
0.1%
30.4 1
 
0.1%
27.2 2
0.2%
26.9 1
 
0.1%
26.7 1
 
0.1%
26.5 1
 
0.1%
26.2 1
 
0.1%
26.1 1
 
0.1%
25.9 3
0.3%
25.8 1
 
0.1%

age_18_19_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct175
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.745645
Minimum5.5
Maximum34.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:06.495358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile8.83
Q112.2
median14.6
Q316.7
95-th percentile22.3
Maximum34.3
Range28.8
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.8263364
Coefficient of variation (CV)0.25948925
Kurtosis1.127881
Mean14.745645
Median Absolute Deviation (MAD)2.2
Skewness0.55301314
Sum13374.3
Variance14.64085
MonotonicityNot monotonic
2023-08-22T13:18:06.626387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.3 24
 
2.6%
15.8 21
 
2.3%
15.4 17
 
1.9%
14.6 15
 
1.7%
14.9 15
 
1.7%
15.3 14
 
1.5%
14 14
 
1.5%
13.8 13
 
1.4%
15.5 13
 
1.4%
15.7 13
 
1.4%
Other values (165) 748
82.5%
ValueCountFrequency (%)
5.5 1
 
0.1%
5.6 1
 
0.1%
5.7 1
 
0.1%
6 1
 
0.1%
6.1 2
0.2%
6.2 1
 
0.1%
6.3 1
 
0.1%
6.4 1
 
0.1%
6.5 1
 
0.1%
6.6 3
0.3%
ValueCountFrequency (%)
34.3 1
 
0.1%
29.9 1
 
0.1%
25.5 1
 
0.1%
25.4 1
 
0.1%
25.1 2
0.2%
24.8 1
 
0.1%
24.6 3
0.3%
24.5 3
0.3%
24.4 2
0.2%
24.3 1
 
0.1%

age_16_24_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.655678
Minimum4.8
Maximum27.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:06.758720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.8
5-th percentile7.33
Q19.8
median11.6
Q313.2
95-th percentile17.3
Maximum27.4
Range22.6
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation2.9225126
Coefficient of variation (CV)0.25073724
Kurtosis1.2238008
Mean11.655678
Median Absolute Deviation (MAD)1.7
Skewness0.55587936
Sum10571.7
Variance8.5410798
MonotonicityNot monotonic
2023-08-22T13:18:06.888750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.8 27
 
3.0%
12 23
 
2.5%
11.1 21
 
2.3%
11.6 21
 
2.3%
12.1 20
 
2.2%
10.8 19
 
2.1%
11.7 19
 
2.1%
12.5 18
 
2.0%
13 18
 
2.0%
10.5 15
 
1.7%
Other values (131) 706
77.8%
ValueCountFrequency (%)
4.8 2
 
0.2%
4.9 1
 
0.1%
5.2 2
 
0.2%
5.3 2
 
0.2%
5.4 2
 
0.2%
5.5 2
 
0.2%
5.6 1
 
0.1%
5.7 2
 
0.2%
5.8 3
0.3%
5.9 5
0.6%
ValueCountFrequency (%)
27.4 1
 
0.1%
25.1 1
 
0.1%
20.4 1
 
0.1%
19.5 1
 
0.1%
19.2 1
 
0.1%
19.1 1
 
0.1%
19 1
 
0.1%
18.9 1
 
0.1%
18.8 3
0.3%
18.7 2
0.2%

age_20_24_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.2868798
Minimum3.5
Maximum25.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:07.015805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.5
5-th percentile5.4
Q17.5
median9.1
Q310.7
95-th percentile14.5
Maximum25.5
Range22
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.7048917
Coefficient of variation (CV)0.29125947
Kurtosis2.0512378
Mean9.2868798
Median Absolute Deviation (MAD)1.6
Skewness0.80949405
Sum8423.2
Variance7.3164392
MonotonicityNot monotonic
2023-08-22T13:18:07.223843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.2 26
 
2.9%
9.1 25
 
2.8%
9.7 22
 
2.4%
8.5 21
 
2.3%
8.6 20
 
2.2%
8.4 19
 
2.1%
7.4 18
 
2.0%
8.7 18
 
2.0%
10 18
 
2.0%
9 17
 
1.9%
Other values (121) 703
77.5%
ValueCountFrequency (%)
3.5 1
 
0.1%
3.6 1
 
0.1%
3.7 2
0.2%
3.8 2
0.2%
3.9 1
 
0.1%
4 1
 
0.1%
4.1 4
0.4%
4.2 4
0.4%
4.3 3
0.3%
4.4 4
0.4%
ValueCountFrequency (%)
25.5 1
0.1%
23 1
0.1%
19.6 1
0.1%
18 1
0.1%
17.2 1
0.1%
16.4 1
0.1%
16.3 1
0.1%
16.2 1
0.1%
16.1 1
0.1%
16 2
0.2%

age_25_34_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4975744
Minimum1.9
Maximum14.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:07.350872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile2.9
Q14.15
median5.2
Q36.7
95-th percentile9.5
Maximum14.5
Range12.6
Interquartile range (IQR)2.55

Descriptive statistics

Standard deviation1.8753292
Coefficient of variation (CV)0.34111938
Kurtosis1.0325756
Mean5.4975744
Median Absolute Deviation (MAD)1.2
Skewness0.89077775
Sum4986.3
Variance3.5168595
MonotonicityNot monotonic
2023-08-22T13:18:07.486912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.3 32
 
3.5%
5.2 32
 
3.5%
5.1 31
 
3.4%
5.8 25
 
2.8%
5 25
 
2.8%
5.4 23
 
2.5%
4.4 23
 
2.5%
4.3 22
 
2.4%
3.7 21
 
2.3%
4.1 21
 
2.3%
Other values (82) 652
71.9%
ValueCountFrequency (%)
1.9 1
 
0.1%
2.1 1
 
0.1%
2.2 4
 
0.4%
2.3 2
 
0.2%
2.4 2
 
0.2%
2.5 3
 
0.3%
2.6 9
1.0%
2.7 7
0.8%
2.8 9
1.0%
2.9 14
1.5%
ValueCountFrequency (%)
14.5 1
 
0.1%
13.4 1
 
0.1%
11.7 1
 
0.1%
11.3 1
 
0.1%
11 1
 
0.1%
10.8 1
 
0.1%
10.7 2
 
0.2%
10.6 5
0.6%
10.4 3
0.3%
10.3 3
0.3%

age_25_54_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.577398
Minimum1.9
Maximum12.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:07.621280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile2.5
Q13.4
median4.3
Q35.5
95-th percentile7.87
Maximum12.8
Range10.9
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation1.5504847
Coefficient of variation (CV)0.33872622
Kurtosis1.4456393
Mean4.577398
Median Absolute Deviation (MAD)1
Skewness1.0176688
Sum4151.7
Variance2.4040029
MonotonicityNot monotonic
2023-08-22T13:18:07.755311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.3 44
 
4.9%
4.2 41
 
4.5%
3.1 36
 
4.0%
4.1 34
 
3.7%
4.4 31
 
3.4%
3.4 29
 
3.2%
3.3 27
 
3.0%
3.6 25
 
2.8%
3.2 24
 
2.6%
4.7 23
 
2.5%
Other values (65) 593
65.4%
ValueCountFrequency (%)
1.9 1
 
0.1%
2 4
 
0.4%
2.1 2
 
0.2%
2.2 10
1.1%
2.3 15
1.7%
2.4 6
 
0.7%
2.5 9
1.0%
2.6 18
2.0%
2.7 14
1.5%
2.8 7
 
0.8%
ValueCountFrequency (%)
12.8 1
 
0.1%
11.5 1
 
0.1%
9.7 1
 
0.1%
9.1 2
 
0.2%
9 1
 
0.1%
8.9 3
0.3%
8.8 5
0.6%
8.7 7
0.8%
8.5 7
0.8%
8.4 4
0.4%

age_35_44_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.214774
Minimum1.7
Maximum11.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:07.883339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile2.4
Q13.2
median4
Q35
95-th percentile7.07
Maximum11.5
Range9.8
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.405116
Coefficient of variation (CV)0.33337874
Kurtosis1.634694
Mean4.214774
Median Absolute Deviation (MAD)0.9
Skewness1.0564285
Sum3822.8
Variance1.974351
MonotonicityNot monotonic
2023-08-22T13:18:08.010368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.8 50
 
5.5%
2.9 36
 
4.0%
3.7 36
 
4.0%
4.1 35
 
3.9%
4 30
 
3.3%
4.4 28
 
3.1%
3.3 27
 
3.0%
3.6 27
 
3.0%
3.9 25
 
2.8%
3.1 24
 
2.6%
Other values (64) 589
64.9%
ValueCountFrequency (%)
1.7 1
 
0.1%
1.8 1
 
0.1%
1.9 5
 
0.6%
2 4
 
0.4%
2.1 15
1.7%
2.2 9
1.0%
2.3 8
 
0.9%
2.4 13
1.4%
2.5 22
2.4%
2.6 17
1.9%
ValueCountFrequency (%)
11.5 1
 
0.1%
10.1 1
 
0.1%
9 2
0.2%
8.8 1
 
0.1%
8.7 1
 
0.1%
8.6 3
0.3%
8.5 2
0.2%
8.3 1
 
0.1%
8.2 2
0.2%
8.1 3
0.3%

age_45_54_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8359427
Minimum1.6
Maximum12.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:08.140388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6
5-th percentile2.2
Q12.9
median3.5
Q34.5
95-th percentile6.47
Maximum12.3
Range10.7
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.3145426
Coefficient of variation (CV)0.3426909
Kurtosis3.1470066
Mean3.8359427
Median Absolute Deviation (MAD)0.7
Skewness1.3413261
Sum3479.2
Variance1.7280224
MonotonicityNot monotonic
2023-08-22T13:18:08.277420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 43
 
4.7%
3.4 43
 
4.7%
3.5 39
 
4.3%
3.2 39
 
4.3%
2.6 38
 
4.2%
3.1 35
 
3.9%
2.8 34
 
3.7%
4 32
 
3.5%
2.7 30
 
3.3%
4.1 30
 
3.3%
Other values (58) 544
60.0%
ValueCountFrequency (%)
1.6 1
 
0.1%
1.7 1
 
0.1%
1.8 5
 
0.6%
1.9 13
1.4%
2 5
 
0.6%
2.1 13
1.4%
2.2 12
1.3%
2.3 22
2.4%
2.4 20
2.2%
2.5 23
2.5%
ValueCountFrequency (%)
12.3 1
 
0.1%
10.7 1
 
0.1%
8.4 1
 
0.1%
8.1 1
 
0.1%
8 1
 
0.1%
7.9 2
 
0.2%
7.8 4
0.4%
7.7 1
 
0.1%
7.6 5
0.6%
7.5 3
0.3%

age_20plus_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0254686
Minimum2.2
Maximum14.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:08.407449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile2.8
Q13.8
median4.8
Q36.05
95-th percentile8.4
Maximum14.2
Range12
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation1.6141557
Coefficient of variation (CV)0.32119506
Kurtosis1.6319774
Mean5.0254686
Median Absolute Deviation (MAD)1
Skewness0.98898506
Sum4558.1
Variance2.6054985
MonotonicityNot monotonic
2023-08-22T13:18:08.545043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.9 41
 
4.5%
4.7 37
 
4.1%
4.8 36
 
4.0%
4.6 32
 
3.5%
4.5 28
 
3.1%
3.8 27
 
3.0%
3.4 24
 
2.6%
5 23
 
2.5%
4 22
 
2.4%
4.1 22
 
2.4%
Other values (68) 615
67.8%
ValueCountFrequency (%)
2.2 1
 
0.1%
2.3 6
 
0.7%
2.4 2
 
0.2%
2.5 1
 
0.1%
2.6 16
1.8%
2.7 13
1.4%
2.8 9
1.0%
2.9 9
1.0%
3 19
2.1%
3.1 7
 
0.8%
ValueCountFrequency (%)
14.2 1
 
0.1%
12.6 1
 
0.1%
10.6 1
 
0.1%
9.9 1
 
0.1%
9.8 1
 
0.1%
9.6 1
 
0.1%
9.5 1
 
0.1%
9.4 1
 
0.1%
9.3 4
0.4%
9.2 5
0.6%

age_25plus_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4338479
Minimum2
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:08.678073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.5
Q13.4
median4.1
Q35.3
95-th percentile7.5
Maximum13
Range11
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.4606052
Coefficient of variation (CV)0.32942158
Kurtosis2.0203691
Mean4.4338479
Median Absolute Deviation (MAD)0.9
Skewness1.0916113
Sum4021.5
Variance2.1333674
MonotonicityNot monotonic
2023-08-22T13:18:08.811094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 48
 
5.3%
4.1 43
 
4.7%
3 31
 
3.4%
4.2 30
 
3.3%
3.2 29
 
3.2%
3.4 29
 
3.2%
3.7 27
 
3.0%
4.4 26
 
2.9%
4.5 26
 
2.9%
4.3 25
 
2.8%
Other values (60) 593
65.4%
ValueCountFrequency (%)
2 2
 
0.2%
2.1 8
 
0.9%
2.2 13
1.4%
2.3 8
 
0.9%
2.4 7
 
0.8%
2.5 12
1.3%
2.6 15
1.7%
2.7 14
1.5%
2.8 12
1.3%
2.9 24
2.6%
ValueCountFrequency (%)
13 1
 
0.1%
11.5 1
 
0.1%
9.7 1
 
0.1%
9 1
 
0.1%
8.6 2
 
0.2%
8.5 1
 
0.1%
8.4 7
0.8%
8.3 3
0.3%
8.2 3
0.3%
8.1 7
0.8%

age_55plus_rate
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8102536
Minimum1.7
Maximum13.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-08-22T13:18:08.936132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile2.4
Q13
median3.6
Q34.4
95-th percentile6.2
Maximum13.6
Range11.9
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.1963219
Coefficient of variation (CV)0.31397436
Kurtosis7.7215523
Mean3.8102536
Median Absolute Deviation (MAD)0.7
Skewness1.8261892
Sum3455.9
Variance1.4311861
MonotonicityNot monotonic
2023-08-22T13:18:09.147180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.1 52
 
5.7%
3.2 46
 
5.1%
3.5 44
 
4.9%
3 41
 
4.5%
2.7 40
 
4.4%
3.9 40
 
4.4%
3.8 36
 
4.0%
2.8 34
 
3.7%
2.6 33
 
3.6%
3.3 32
 
3.5%
Other values (50) 509
56.1%
ValueCountFrequency (%)
1.7 1
 
0.1%
1.9 4
 
0.4%
2 9
 
1.0%
2.1 6
 
0.7%
2.2 6
 
0.7%
2.3 11
 
1.2%
2.4 13
 
1.4%
2.5 19
2.1%
2.6 33
3.6%
2.7 40
4.4%
ValueCountFrequency (%)
13.6 1
 
0.1%
11.8 1
 
0.1%
9.6 1
 
0.1%
8.8 1
 
0.1%
7.6 1
 
0.1%
7.4 1
 
0.1%
7.2 3
0.3%
7.1 2
 
0.2%
7 5
0.6%
6.9 4
0.4%

Interactions

2023-08-22T13:18:03.670153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.165073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.363427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.546343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.784992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.998266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.218542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.371791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.640623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.804127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.032912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.200227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.416870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.767175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.261095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.456447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.712380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.881013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.090286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.310563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.465812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.734262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.895147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.124933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.295249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.509900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.855195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.351115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.540459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.797400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.971034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.178297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.395582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.554832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.820281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.982158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.210953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.387260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.669927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.946225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.441136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.629477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.883419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.058052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.263316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.482601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.644852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.907291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.068177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.297972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.476281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.757946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.041246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.538157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.722157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.974448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.153065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.426363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.573622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.740419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.998945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.161198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.392993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.574303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.853978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.130267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.627177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.810186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.067470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.243095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.509380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.657632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.830439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.084964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.248218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.480013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.664331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.939997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.219277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.716198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.895205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.153480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.332115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.594401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.742660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.919460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.172984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.333237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.568024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.755353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.028018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.314308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.810219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.994218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.245510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.429137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.685420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.833681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.016482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.265996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.426258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.660054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.851751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.121039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.405329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.900239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.087239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.334531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.521158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.773441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.921701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.181509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.355016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.516279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.750064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.942772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.212049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.492348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:49.989259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.174259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.421550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.610178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.858460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.006720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.269529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.441036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.600297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.835084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.039785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.299070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.585370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.081280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.267280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.509570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.704199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:54.947481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.095740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.359549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.528064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.688317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:00.925165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.131806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.390099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.680391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.177302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.360301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.602591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.799221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.036500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.187752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.453580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.621085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.779855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.018177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.226826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.485111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:04.769411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:50.269406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:51.452322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:52.691971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:53.891242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:55.126511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:56.276769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:57.544601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:58.709105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:17:59.867875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:01.109206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:02.318847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-22T13:18:03.578132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-22T13:18:09.244201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
overall_rateage_16_17_rateage_16_19_rateage_18_19_rateage_16_24_rateage_20_24_rateage_25_34_rateage_25_54_rateage_35_44_rateage_45_54_rateage_20plus_rateage_25plus_rateage_55plus_rate
overall_rate1.0000.8280.8870.8890.9640.9690.9690.9670.9420.9080.9880.9620.813
age_16_17_rate0.8281.0000.9680.8980.9070.8330.8160.7860.7700.6860.7990.7650.563
age_16_19_rate0.8870.9681.0000.9760.9580.8920.8750.8510.8380.7630.8640.8340.646
age_18_19_rate0.8890.8980.9761.0000.9480.8980.8870.8680.8570.7940.8760.8540.685
age_16_24_rate0.9640.9070.9580.9481.0000.9700.9310.9160.8990.8390.9410.9050.736
age_20_24_rate0.9690.8330.8920.8980.9701.0000.9600.9500.9320.8810.9690.9400.780
age_25_34_rate0.9690.8160.8750.8870.9310.9601.0000.9890.9630.9210.9860.9790.807
age_25_54_rate0.9670.7860.8510.8680.9160.9500.9891.0000.9840.9590.9920.9960.855
age_35_44_rate0.9420.7700.8380.8570.8990.9320.9630.9841.0000.9500.9720.9850.867
age_45_54_rate0.9080.6860.7630.7940.8390.8810.9210.9590.9501.0000.9440.9690.920
age_20plus_rate0.9880.7990.8640.8760.9410.9690.9860.9920.9720.9441.0000.9890.853
age_25plus_rate0.9620.7650.8340.8540.9050.9400.9790.9960.9850.9690.9891.0000.888
age_55plus_rate0.8130.5630.6460.6850.7360.7800.8070.8550.8670.9200.8530.8881.000

Missing values

2023-08-22T13:18:04.903441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-22T13:18:05.097485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

dateoverall_rateage_16_17_rateage_16_19_rateage_18_19_rateage_16_24_rateage_20_24_rateage_25_34_rateage_25_54_rateage_35_44_rateage_45_54_rateage_20plus_rateage_25plus_rateage_55plus_rate
01948-01-013.49.48.58.36.85.83.02.52.02.23.02.62.9
11948-02-013.813.110.08.27.76.33.32.92.52.83.32.93.1
21948-03-014.013.010.58.98.77.62.92.82.72.63.52.83.0
31948-04-013.911.29.58.67.86.83.43.02.92.63.53.03.0
41948-05-013.56.57.07.96.76.63.02.72.62.43.32.83.1
51948-06-013.611.99.37.17.36.03.02.72.62.43.22.72.8
61948-07-013.610.39.79.37.56.22.92.62.52.53.12.72.8
71948-08-013.99.09.69.77.15.73.63.12.82.73.43.13.3
81948-09-013.89.18.88.26.75.53.43.12.73.23.43.13.2
91948-10-013.78.18.58.66.45.23.42.92.52.63.42.93.2
dateoverall_rateage_16_17_rateage_16_19_rateage_18_19_rateage_16_24_rateage_20_24_rateage_25_34_rateage_25_54_rateage_35_44_rateage_45_54_rateage_20plus_rateage_25plus_rateage_55plus_rate
8972022-10-013.79.811.011.98.16.94.03.22.92.83.43.02.4
8982022-11-013.611.511.311.38.26.84.13.22.62.73.33.02.5
8992022-12-013.58.410.412.28.27.33.82.92.42.33.22.82.7
9002023-01-013.410.910.310.08.07.13.93.02.62.33.22.82.3
9012023-02-013.69.011.112.18.16.93.93.12.62.63.32.92.5
9022023-03-013.59.19.810.37.56.53.82.92.52.43.22.92.6
9032023-04-013.49.49.29.46.55.43.83.12.92.43.22.92.3
9042023-05-013.79.510.310.67.46.33.93.12.92.63.43.02.8
9052023-06-013.611.211.010.57.56.13.93.12.92.43.33.02.6
9062023-07-013.511.211.311.48.06.73.63.03.02.33.22.82.3